Implementation of the virtual teamworking concept into the
simulation project life-cycle.
BANASZAK, Jakub.
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Implementation of the Virtual Teamworking
Concept into the Simulation Project Life-Cycle
Jakub Banaszak
A thesis submitted in partial fulfilment of the requirements of Sheffield Hallam University for the degree of Doctor of Philosophy
Preface
This thesis is submitted to the School of Engineering of Sheffield Hallam University for the degree of Doctor of Philosophy.
I would like to express my deepest gratitude and appreciation to my supervisors Dr. D.T.S. Perera and Dr D.R. Clegg (School of Engineering) for their guidance, help and constructive criticism during the course of this study. I would like to thank my family and friends, in particular to my wife Agnieszka for her patience and support. I would also like to thank my colleagues and administrative staff within the School of Engineering, and the Research Office for their help and support.
The results obtained during the course of this research are the best to my knowledge and original, except where reference is made to the work of others.
Abstract
Introduction...8
1 Literature Review...13
1.1 Introduction...13
1.2 Simulation project... 13
1.2.1 System and modelling paradigm...13
1.2.2 Types of simulation models... 14
1.2.3 Purpose of using the simulation...15
1.2.4 The benefits of using simulation in industry... 15
1.3 Procedures for conducting a simulation project... 16
1.3.1 Law and Kelton’s procedure... 16
1.3.2 Balci and Nance’s procedure... 19
1.4 Simulation Team and Team Working...20
1.4.1 Characteristics of successful team... 20
1.4.2 Result-driven structure...21
1.5 Simulation Team structure...22
1.5.1 Problem Resolution Teams...22
1.5.2 Creative Teams... 23
1.5.3 Simulation teams... 23
1.6 The Internet impact on simulation...24
1.6.1 Web-based simulation...25
1.7 Technology in Virtual Team...28
1.7.1 Social Presence...29
1.7.2 Information Richness...30
1.7.3 Other Factors...30
1.7.4 Available Technologies...31
1.7.4.1 Desktop and real-time data conferencing... 32
1.7.4.2 Electronic meeting system (EMS)... 32
1.7.4.3 Video conferencing... 33
1.7.4.4 Audio conferencing... 33
1.7.4.5 Messaging systems... 34
1.7.4.6 E-mail...34
1.7.4.7 Group calendars and Schedules...34
1.7.4.8 Bulletin boards and Web pages... 34
1.7.4.9 Non-real-time database sharing and conferencing...35
1.7.4.10 Workflow application... 35
2 Research methodology and preliminary work... 36
2.1 The research process... 36
2.2 Summary of the deployed research methods...38
2.2.1 Questionnaire Survey...38
2.2.2 Questionnaire development and deployment...39
2.2.3 Questionnaire results...39
3 Virtual Team Technology... 43
3.1 Definition and characteristics of virtual team... 43
3.2 Types of virtual teams...44
3.3 Critical Success Factors for Virtual Teams... 45
4 Proposed methodology...47
4.1 Definition of methodology... 47
4.2 The rationale for a methodology...48
4.4 Developing methodology for virtual simulation teamworking...49
4.4.1 Setting goals and objectives for the virtual simulation team...50
4.4.2 Principled leadership... 50
4.4.3 Members team selection and their roles in team building and project...51
4.4.4 Selection of technology... 53
4.4.5 Team trust building...53
4.4.6 Alignment of processes to the virtual environment...54
4.4.7 Performance measures... 55
4.4.8 Reward system... 55
4.4.9 Members training ... 56
4.4.10 Security issues... 56
4.4.11 Virtual team facilitator... 56
4.5 Develop the framework for effective simulation virtual teamworking... 57
4.5.1 Team working factors... 58
4.5.2 Simulation project factors...58
4.5.3 People factors... 59
4.5.4 Technology factors...60
4.6 Methodology for carrying out a simulation project in a virtual environment 62 4.6.1 Development of the simulation model... 63
4.6.2 Development of a Virtual Simulation Team...63
4.7 Project initiation...65
4.7.1.1 Project Specification...65
4.7.1.2 Establishing the Virtual Team... 65
4.7.1.3 Project Management and Control... 66
4.7.1.4 Project Completion...67
4.8 Redesigning the meeting structure for virtual simulation teams... 67
4.8.1 Short term recommendation...68
4.8.2 Medium term recommendation... 69
4.8.3 Long term recommendation...69
4.9 Validation of the methodology... 70
5 Developing technology for support virtual simulation team... 71
5.1 Introduction... 71
5.2 Preliminary investigation - Determine the problem...73
5.2.1 Impetus for change... 73
5.2.2 Management support... 73
5.2.3 Problem definition...73
5.2.4 Problem Scope...73
5.2.5 System Objectives...74
5.3 Analysis - Understanding the system...74
5.3.1 Gathered data... 74
5.3.2 System requirements... 74
5.3.3 Understanding of the system... 75
5.4 Design - Plan the new system...76
5.4.1 Preliminary design... 76
5.4.2 Design Concept...79
5.4.2.1 Requirements for management data system and project documentation. 79 5.4.2.2 Database Management System (DBMS)... 80
5.4.2.3 Data distribution ... 82
5.4.2.4 Data collection... 82
5.4.2.6 Remote execution of simulation models...83
5.4.3 Detail Design...87
5.4.3.1 System Functionality...89
5.5 Development... 91
5.5.1 Developing the application...91
5.5.1.1 Proj ect documentation... 92
5.5.1.2 Proj ect and meetings schedule... 93
5.5.1.3 Model execution...93
5.5.1.4 Review simulation results...94
5.5.1.5 Virtual meeting... 95
5.5.1.6 Team members' feedback...96
5.5.1.7 Asynchronous communication... 97
5.5.1.8 Synchronous communication...97
5.5.1.9 Collect data...98
5.5.1.10 H elp...98
5.5.2 Testing the application...99
5.6 Implementation...100
6 Empirical validation of the methodology and technology for virtual teamworking in a simulation proj ect... 101
6.1 The experimental virtual simulation team...101
6.2 The objectives of the experiment...102
6.3 Simulation Proj ect...102
6.4 First meeting - creation of the virtual simulation team... 103
6.4.1 The structure of the first meeting... 103
6.4.2 The outcomes of the first meeting... 104
6.5 Virtual meetings and outputs... 106
6.6 Validation of the proposed framework... 106
6.6.1 TeamWorking...109
6.6.2 Technology... 110
6.6.3 People...110
6.6.4 Simulation... I ll 7 Simulation of the different team working approaches in simulation project lifecycle -analytical validation of the virtual simulation team methodology...112
7.1 Problem definitions and objectives sets up...112
7.2 Simulation models...114
7.3 Design Experiment...117
7.4 Conducting Experiment & Analysis of the Results...119
7.5 Limitation of the results...130
7.6 Conclusions... 130
8 Research results, conclusions and future work...132
8.1 Research question 1: "How can the Internet based solutions be applied in the life cycle of simulation project in order to improve efficiency of the simulation team?".... 132
8.2 Research question 2: "How do we establish virtual simulation team?"...133
8.3 Research question 3: "How can we apply the virtual teamworking concept into the simulation project life-cycle?"...134
8.4 Research question 4: "What technology should be used to support the virtual simulation team?"...135
8.5 Research question 5: "What are the implications of virtual teamworking on a simulation proj ect?"... 135
8.7 Future work...138 Reference... 139 Appendix A - The framework for applying the virtual team concept into a simulation
Introduction
Simulation is a powerful and well established tool that has the capability of producing the best solution for a variety of design and operational issues in manufacturing systems. It provides the ability to assess the impact of various solutions without interfering with the concerned real system. Law and Kelton (1991) argue that the simulation can significantly decrease the cost and risk of implementing a new solution, and at the same time speed up the process of analysing and finding the optimum solution.
Typically, simulation projects are complex, design to tackle a specific situation or problem, and involve a number of people in the developing process. The simulation study requires cooperative work and inputs from all parties involved in. The simulation team usually is formed with the specific roles for team members to play such as project leader, model builder, data provider, customer, consultant, etc.
However, the globalisation of business operations means that individuals involved in a large multi-site simulation project may be physically dispersed across the organisation and the world. For example, simulation experts may be based in one location and their service may be offered to business units scatted across the globe. The different locations of parties involved in a simulation project implicate time and cost consuming travelling operations to meetings and back, which not add value to a project. In order to eliminate the waste in a process of a simulation model development there is a call for applying the modem Internet-based communication technologies in the simulation teamworking.
The development in communication technologies has significantly affected the way that modem businesses work. In recent years, companies have successfully deployed the Internet based technologies to improve their business function as well as expand technological systems. The enterprises IT systems have been integrated with Internet technologies to improve the gathering and distribution of business information, and apply across the enterprises to communicate day-to-day activities.
that there is no need for physical co-location of team members; instead modem communication technologies enable geographically dispersed team members to function as a co-located team.
The rapid expansion of the Internet has drawn the attention of academics, practitioners, and vendors involved with simulation. Special conferences have been organised (like for example WEBSIM), and a number of projects investigate the implications of Web, as well as developing new applications. It also appears that virtual teamworking concept can be applied into a simulation team. This eliminates the need for face-to-face meetings; interactions between team members are managed using modem communication tools enabling them to operate as a co-located team. In author's opinion it should also reduce time waste and cost produced by working in traditional simulation team in the new global market.
The successful transition from the traditional simulation team into virtual simulation team requires developing a methodology and procedures. However, reported guidelines and methodologies for setting up virtual teams are primary targeted at general business function, like Lipnack and Stamps (1997) or Duarte and Snyder (1999) publications. The engineering approach presented by Bal and Teo (2001), Orsak and Etter (199.6); or IT application presented by Edwards and Sridhar (2003) cannot be simply applied in a simulation project. Considering different characteristics of the simulation project, which mainly is the development of a computerised simulation model; in authors opinion it is required to develop a methodology for setting up a virtual simulation team.
The project investigates the implication of virtual teamworking on a simulation project that it is concluded by the proposition of a new methodology for creating and maintaining virtual simulation team. The proposed methodology has guidelines to follow to establish from a group of people with different priorities and background an efficient and creative virtual team.
In order to examine the proposed methodology two validation methods were developed: 1. Analytical methods - Simulation models have been applied to compare effectiveness of
different collaboration scenarios in a simulation project.
2. Empirical methods - Following the recommendation presented in the previous chapters a virtual team has been created to confront a real problem using simulation models and the developed methodology.
development process emphasis was put on such factors as cost, ease of maintenance, user-friendliness, communication and data transfer. The created application uses the standard WWW client-server technology with a support database and link to simulation software, which allows the project participants to cooperate by using one of the popular Web-browsers.
The aim of this project was to investigate implications of applying the virtual teamworking concept into simulation project life-cycle. The study was focused around five research questions, which were generated by literature review and survey's results:
(1) How can the Internet based solution be applied in the life-cycle of simulation project in order to improve efficiency of simulation team?
(2) How do we establish a virtual simulation team?
(3) How can we apply the virtual teamworking concept into the simulation project life-cycle?
(4) What technology should be used to support the virtual simulation team? (5) What are the implications of virtual teamworking on a simulation
project?
As the result of this study the new methodology for establishing virtual simulation team was developed and validated. The methodology is based on the proposed new framework for effective virtual simulation teamworking
Chapter 1 in its first part introduces the simulation concept, rules and life-cycle. The advantages of team driven structures are presented and the typical structure and members of the simulation team are illustrated. The last part describes the implication of Internet technologies on simulation, which concludes in the first research questions about the consequence of the development of Internet technologies on the simulation project. In this chapter also a modem communication and collaboration technology is introduced, and technology selection factors discussed.
the simulation, methodology for establishing the virtual simulation team, and necessary support technology.
Chapter 3 introduces the concept of the virtual team, its characteristics, types and critical success factors. The potential benefits of virtual teamworking are also discussed.
Chapter 4 emphasises the need for developing the methodology for creating the virtual simulation team. The influential factors are discussed that drives the development of the framework for effective simulation virtual teamworking. The proposed methodology is presented and an implication on the simulation project discussed. At the end the methodology's validation process is proposed.
Chapter 5 introduces the development process of a Web-based application to support the simulation virtual team. The chapter follows through the whole process from the set up of the objectives, design, building, testing, to the final revision.
Chapter 6 presents the outcomes of applying virtual teamworking into the simulation project. To evaluate the methodology the problem was stated, the virtual simulation team formed and collaboration between participants was obtained by the developed application. The data collected during the project was used to validate the methodology and the technology.
Chapter 7 reviews the process of the analytical revision of the virtual teamworking in the simulation project. It describes the simulation analysis carried out to compare the traditional team concept with the virtual one. The results are presented and discussed.
Chapter 8 discusses repercussions of virtual teamworking on the quality of the simulation project. The concept of quality in simulation project is introduced and the possible implication of communication technologies investigated.
1 Literature Review
1.1 Introduction
This chapter presents a background and history of simulation technology by a review of the literature. It presents documented approaches to the development of simulation models and simulation model life cycles. It also describes rules for the members of the simulation project team. This section is followed by a review of documented impact of the Internet technologies on the simulation techniques and project. The chapter concludes by describing the focus of this study and the resulting first research question, which is answered in the subsequent chapters of this thesis.
1.2 Simulation project
Simulation is a tool that allows the creation of a model of the system, which mimics reality. It can be executed on a computer machine to enable experiments to be conducted with the aim of studying the behaviour of the system with different variables affecting it. Moreover applying a computer to calculate the simulation model allows us, in a relatively short time, to observe and predict the behaviour of the system over the long period of time. The impact of a change in examining system factors can be monitored quickly and easily, enabling managers to explore a range of options without impacting on the system itself (Robinson 1994).
However, in the first place, the simulation analysis requires the development of some kind of model, which becomes the abstraction of the system. The model has to reflect the system with accuracy and methods adequate to interaction in it. In the next step a series of experiments are conducted where the variables in the model are changed to reflect the intended changes to the system. The analysis of the results will help to choose the most acceptable and profitable solution.
1.2.1 System and modelling paradigm
design stage, playing with system may be impossible, unwise or too expensive (ex. air traffic system).
Schmidt and Taylor (1970) define a system as a collection of entities e.g., people or machines that interact together toward the accomplishment of some logical end. Banks (1984) describes a system as a group of objects that are joined together in some regular interaction or independence toward the accomplishment of some purpose. However Law and Kelton (1991) indicate that in practice, the system in question depends on the objective of the simulation study and they represent the system stage as being a collection of variables necessary to describe a system at a particular time.
1.2.2 Types of simulation models
A simulation project involves building a model of the system to be studied, which Banks and Carson (1984) defined as a representation of a system for the purpose of studying the system. Mihram and Michram (1974) pointed out that a model is not only the substitute for a system, but it is also a simplification of it. On the other hand, the model must be adequately detailed to permit proper analysis and valid conclusions to be obtained about the real system. Robinson (1994) concluded that the basic rule is to include in a model the minimum amount of detail required to achieve the project’s objectives.
According to Pidd (1992), there are two types of models - physical and mathematical. Physical or iconic models are usually the physical structure that represented the real system at reduce scale (For example, the model of the aircraft in the wind tunnel.). However, the mathematical models use symbolic notation and mathematical equations to represent a system.
Simulation models can be further classified as being static or dynamic, deterministic or stochastic, and discrete or continuous. A static simulation model represents a system at a particular point of time while a dynamic simulation model represents a system as it changes over time. A simulation model that does not contain random variables is classified as deterministic. While a stochastic simulation model has one or more random variables as inputs.
type of change predominates for most of the system, it is usually possible to classify a system as being either discrete or continuous. They also focused on the fact that the objectives of the simulation project strongly determine the choice of simulation techniques.
1.2.3 Purpose of using the simulation
Banks and Carson (1984) presented a number of reasons why it may be preferable to carry out experiments on a model rather than directly on the real systems:
1. Simulation allows the study and experimentation with the internal interactions of a complex system, or of a subsystem within a complex system.
2. Informational, organisational and environmental changes can be simulated and the effect of these alterations on the model’s behaviour can be observed.
3. The knowledge gained in designing a simulation model can be of great value towards suggesting improvement in the system under investigation.
4. By changing simulation inputs and observing the resulting outputs, valuable insight may be obtained into which variables are most important and how variables interact. 5. Simulation can be used as a pedagogical device to reinforce analytic solution
methodologies.
6. Simulation can be used to experiment with new designs or policies prior to implementation, so as to prepare for what may happen.
7. Simulation can be used to verify analytic solutions.
1.2.4 The benefits of using simulation in industry
Robinson (1984) describes the simulation as one of the most powerful operational research techniques with potential benefits such as:
□ Risk reduction
These benefits were realised by the deployment of simulation to support the application presented in Table l-l(Tye 1999).
Base = 65 Current/Past Users % Plant Layout and Utilisation 77 Analysing Material Control Rules 66 Analysing Required Manning Levels 65 Short Term Scheduling and Loading 60 Capital Equipment Analysis 52
Line Balancing 51
Inventory Evaluation and Control 49 Information Flow Analysis 40 Process Definition and Analysis 35
Table 1-1 Deployment of simulation in industrial application (Tye 1999)
Cohran et al. (1995) conclude that the most common application for simulation in US industry is design (facility design, system development and design), closely followed by research (product development, industry modelling) and then scheduling (shop floor workflow analysis, and prioritising).
1.3 Procedures for conducting a simulation project
A simulation process life cycle has been documented by a number of practitioners since the early stage of the technology. This section details two of them: Law and Kelton’s procedure, and Balci and Nance’s procedure. However it must be mentioned that other authors such as Banks and Carson (1984), Robinson (1994) or Gass (1987) also had presented their approaches.
1.3.1 Law and Kelton’s procedure
[image:19.614.147.427.90.309.2]Steps of a simulation project life cycle
1. Formulate the problem and plan the study. This step involves setting up the objectives of the study and development of the plan and schedule, which describes the required number of people and time for each aspect of the project.
2. Collect data and define a model. If the system exists, the function of this step is to collect data to specify operating procedures and probabilities distribution for random variables used in the model. If the system is in design stage the data must be estimated from the project assumption or other possible sources.
3. Valid? The authors believe that validation should be carried throughout the entire project. However, they propose that there are a number of points during the study where validation is particularly appropriate and essential. They pay attention to the concept of model validity and credibility to itself and the decision-maker. To achieve validity and credibility of the model, it is important to involve the decision-makers and model end-user on regular basis.
4. Construct computer programme and verify. The modeller has to make a choice between programming a model in a general-purpose language or a simulation language.
5. Make pilot runs. Pilot runs allow the modeller to conduct a process of analysis of input data to determine the accuracy of input data and to compare the output data to values from the real system.
6. Design experiment. To evaluate different system scenarios, it is necessary to design a series of experiments to test the system. The authors note that often, a complete decision regarding the number and type of experiments can be made at this stage, but data from experiments may generate additional experimental requirements.
7. Make production runs. In this stage the model is run to generate performance data for each experiment
8. Analyse output data. The results from the previous step are analysed using statistical methods. Confidence intervals can be constructed and data from different systems can be compared.
no Valid ?
yes
no Valid ?
yes
Collect data and define a model
Design experiments Construct a computer
program and verify
Make pilots run
Make production runs
Analyse outputs results
Document present, and implement results Formulate problem and
[image:21.612.140.362.43.513.2]plan the study
1.3.2 Balci and Nance’s procedure
Balci and Nance’s simulation process procedure (Figure 1-2) consists of ten phases (Balci and Nance 1990), each phase representing an outcome of the process, indicated by the arrows connecting each phase. They pointed out that the simulation process life cycle is not a sequential process, but reverse steps may be taken when errors occur. They also dealed with issues concerning validation and verification at various stages of the project, in particular identifying appropriate validation and verification techniques for the different phases of the project.
Problem Formulation
System Investigation
Model Formulation
Model Representation
Model Validation
Data Validation
Programming
Design of Experiments SIMULATION
RESULTS
EXPERIMENTAL MODEL
CONCEPTUAL MODEL
PROGRAMMED MODEL
COMMUNICATIVE MODEL(S) FORMULATED
PROBLEM COMMUNICATED
PROBLEM
PROPOSED SIMULATION
TECHNIQUE
SYSTEM AND OBJECTIVES DEFINITION
Figure 1-2 Balci and Nance’s procedure (based on Balci and Nance 1990)
[image:22.615.67.493.208.639.2]• Project/Objective definition, • Model building and testing • Experimentation
• Project completion and documentation.
The literature review also stressed the requirements for carrying the verification and validation procedures at every stage of the project. The identified main stages of simulation project are used in experiment described in Chapter 7.
1.4 Simulation Team and Team Working
Because the concept of the simulation team is applied in farther research following subchapter recapitulates the characteristics of the teams, team working and simulation team.
Successful simulation projects require strong teams and full participation from every individual involved in the project. Every team member must buy into the process by understanding where the project is going and what is required of them for it to be a success.
Benefits of collaborative and collective effort to overcome problems
Teams produce a greater quantity of ideas and information than individuals acting alone
Teams improve understanding and acceptance among individuals involved in the process
Teams create higher motivation and performance levels than individuals acting alone
Teams offset personal biases and blind spots that hinder the decision process
Teams sponsor more innovative and risk taking decision-making.
Table 1-2 Benefits of teamwork (Mayer 1967)
1.4.1 Characteristics of successful team
Hirschom (1991) identified the characteristics and property of efficient functioning teams: - Clear, elevating goals
[image:23.614.87.486.364.587.2]- Unified commitment - A collaborative climate - Standards of excellence
- External support and recognition - Principal leadership
Larson and LaFasto (1989) and Bennis and Nanus (1986) noticed that the more an individual or a group of people have a clear understanding of the nature of the problem that confronts them, its worth and importance, the more effective they will be in looking for a solution. But when goals become unfocused or politicised, the team lost it’s sense of urgency or priority about its objective, the team’s effort become divided, too many other competitive goals, or individual goals take priority, the whole teamwork become inefficient and painful for members of the team.
Briefly, the clarity of the goals implies there is a specific performance objective, phrased in such concrete language that it is possible to tell, unequivocally, whether or not that performance objective has been attained (Leigh and Maynard 1995).
The goal can be personally challenging to the individual and/or collective effort and also can be elevating because it challenges-stretching the limits of physical and mental abilities of team members (Chang 1995). It offers an opportunity to excel. However the goal can be evaluated in the sense that the performance objective itself makes a difference - creating a sense of urgency and importance.
1.4.2 Result-driven structure
The properly organised team should have a specified structure with responsibilities and communication channels for the co-ordination of its activities. The importance of a defined structure becomes especially visible and painful during any disaster or crisis. However, the effective structure is more than merely having the basic components in place. The significance of a structure lies in identifying the appropriate structure for the achievement of a particular performance objective. A specific configuration that does not confuse effort with results and that makes sense to the team members involved.
number of alternative team structures, which Larson and LaFaste (1989) divided into three main kinds (Table 1-3): problem resolution, creative and tactical.
Broad Objective Dominate
feature Process emphasis
Problem resolution Trust Focus on issue
Creative Autonomy Explore possibilities and alternatives
Tactical Clarity Directive
Highly focused task Role clarity
Well-defined operational standards Accuracy
Table 1-3 Basic structures of team (Based on Larson and LaFaste 1989)
1.5 Simulation Team structure
The structure of a simulation team is described in this subchapter, as the reorganization of a simulation team into a virtual simulation team is the subject of that research.
Simulation is usually used to solve problems that appear in systems. To look for optimal parameters to control systems a simulation team should be organised as a problem reduction team. However a creative simulation team can be used as a support tool during the designing of a new system.
1.5.1 Problem Resolution Teams
A team is organised to resolve problems on an ongoing basis. When this is the broad purpose of the collective team effort, the most important and necessary feature is trust. Each member of the team must expect, and believe, that interactions among members will be truthful and embody a high level of integrity. Also the members must believe that the team will be fairly consistent and mature in its approach to dealing with problems.
1.5.2 Creative Tearns
When the broad objective of the team emphasises creativity, then a necessary feature of the team’s structure is autonomy. The process focuses the creative team on exploring possibilities and alternatives. However for creative team to function, it is necessary to have autonomy from systems and procedures, as well as to create an atmosphere in which ideas can be developed and promoted (Larson and LaFaste 1989).
1.5.3 Simulation teams
The simulation team project should consist of people who are specialists in their discipline, representing a high level of competence and commitment. However the personal predisposition of people to work as a member of the group also needs to be considered (Nastings et al. 1986). Figure 2.4 shows seven roles that typically exist in any simulation study.
Team leader Client
M odel user
M odeller
M odelling supporter
Data provider
Figure 1-3 Team participants in simulation project life cycle (Robinson 1994)
The team leader. Team leadership is vital if the direction of the project is to be set, the
The Client is project sponsor and the recipient of the results. Clients have identified a problem and seek a solution through simulation. They could be the board of directors, a manager, an operator or an external customer. It also may happen that the project has more than one client with each having different opinions concerning the problems and their potential solution.
The Modeller builds and tests the simulation model. Modellers need to have gained
expertise in the software package. They can be a full time simulation expert or work temporarily on simulation for the duration of the project, alternatively a consultant could be employed to perform the modelling role.
The Model User is the person who will use the simulation model in the future, after
completing the project. The model may be passed to a user for experimentation. The user is close to the problem and so well placed to seek a solution but users do not need to have the necessary skills to build their own models. However, they need to be competent in performing experiments and analysing results.
The Data Provider is an expert in the system being modelled and either has direct access to
the data or knows where it can be found. Because simulation requires a great deal of data (including layout, timings, flows, control logic and constraints), in more complex studies more than one data provider may be required.
The Modelling Suvvort is required to join the team and support the simulation process in a
more complex problem. That person supports the team in such aspects as model building, model testing and experimentation. Modelling support can be obtained from the software vendor, consultants or in house expertise.
1.6 The Internet impact on simulation
That subchapter recapitulates the data obtained during the literature review on the subject of implications made by Internet technologies on the simulation technology and methodology.
1996). It becomes not only a useful scientific or business tool but also the place of fun and joy with high-quality graphics, multimedia, and personal Web-sites.
The possibility, connectivity and resources offered by the Internet represent an enormous opportunity for business and its innovation. Cronin (1994) pointed out that even the smallest company could use the network to exchange data with customers or suppliers on the other side of the world. The Internet technologies, with its communication tools like e-mail, newsgroup, or chat room, have revolutionised the collaboration and communication between companies, organisations, and people. It also offers an unprecedented and easily obtained access to the outside world information sources. This information and its creative applications provide the crucial new opportunities for organisations to move ahead of their competition. In order to make better decisions, managers and employees require updated information about situation and trends and the marketplace. To confirm the foregoing words I quote Peter Drucker (1993), a management guru, who said that the most important source of information comes not from internal data but from the outside world.
The following subchapter describes the impact of the Internet technologies on simulation methodology.
1.6.1 Web-based simulation
The emergence of the World Wide Web (WWW) and its related technologies as HTML, HTTP, CGI, etc, has produced an environment within which many disciplines are re evaluating their inherent approaches, techniques and philosophies. According to Page and Opper (2000) the disciplines concerned with computer simulation are no exception and the concept of “web-based simulation” becomes the subject of much interest to both the simulation researcher and simulation practitioners. Since 1996 the web-base simulation has a special panel session at the Winter Simulation Conference, which is the largest annual gathering of simulation professionals in the world. Moreover in January 1998 the first conference dedicated to the topic of web-based simulation (WEBSIM 98) was held as part of the annual Society of Computer Simulation (Fishwick et al 1998).
is no doubt that in net-based electronic business, simulation will be a strategic competitive advantage, and skills, research and tools on this subject will become very important.
Kuljis and Paul (2000) describe the Web as a truly democratic and non-exclusive medium that can become an operating system and a distribution channel for applications, which is easy to use and navigate through. According to Kalakota and Whinston (1997) it creates a new publishing medium, a new distribution model environment, and enables new intra business applications.
Banks and Chair (2000) presented the advantages of moving simulation into virtual reality where consultants and clients would both benefit from web-based simulation capability. Models could be reviewed with clients via Internet during model development. A consultant could make changes to a model via Internet without travelling to the client’s side. Data files could reside in one central place for access by the model from any location in the client network, Models could be shown to a large audience via the Internet during a single session. Web-enabled simulation would also reduce the cost of software maintenance while at the same time increasing the use of the simulation software. Furthermore Jain (1999) pointed at possibility of the integration of simulation systems, manufacturing planning and scheduling systems into decision support systems across the Internet. Virtual teamworking philosophy would allow moving collaboration and communication during the simulation project life cycle on an electronic platform.
Fishwick (1996) identified several potential impacts of web technologies on simulation, with attention given to three key areas:
1. Education and training (ex. Tam et al. 1999, Bender et al. 2000, Ferrero and Piuri 1999).
2. Publication (ex. Mohtar et al. 2000)
3. Simulation programs (Java-based solutions)
However, Page (1998) extended Fishwick categories, and distinguishes five primary areas of web-based simulation:
1. Simulation as hypermedia. Text, images, audio, video simulation - the nature of the
focus on distance learning and interactive, simulation-based education and training are emerging.
2. Simulation research methodology. The ability to rapidly disseminate models, results
and publications on the web permits new approaches to the conduct of simulation research, and scientific research in general. The practical, economic and legal issues associated with the electronic publication of documents, for example, are numerous (Samuelson 1996). The electronic publication of simulation models raises additional considerations.
3. Web-based access to simulation programs. Most commonly associated with the term
web-based simulation, this area includes both the remote execution of existing (so-called “legacy”) simulations from a web browser through HTML forms and CGI (Common Gateway Interface) scripts, and the development of mobile-code simulations (e.g. applets) that run on the client side (Yang 1999).
4. Distributed modelling and simulation. This area includes activities that deal with the use of the WWW and web-oriented technologies (e.g. COBRA, Java RMI) as infrastructure to support distributed simulation execution (Klein et al. 1998, Page et al. 1997, Sajoughian and Ziegler 1998). Internet gaming is included here, as is research in tools, environments and frameworks that support the distributed (collaborative) design and development of simulation models (Cubert and Fishwick 1997)
5. Simulation on the WWW. Modelling and analysis of the WWW for performance characterisation and optimisation.
However Taylor (2000) focused the potential impact of the Internet-based collaboration and communication technologies on a simulation project life-cycle. He recognised that Computer Supported Cooperative Work (CSCW) and Groupware technologies could redesign the interactions between parties involved in a simulation project. He also pointed that frequent meetings of simulation team can could lead to extended project times and high final cost and investigated the usefulness of the NetMeeting software in the process of the collaborative model development (Taylor 2001).
Research questions:
How can the Internet based solutions be applied in the life-cycle of
simulation project in order to improve efficiency of the simulation team?
1.7 Technology in Virtual Team
As the study progress the author had to choose the appropriate technology to support activities in a virtual simulation team and available technology is described in the following subchapter.
The network based applications created new rich methods for communication and collaboration process between parties involve in simulation project. However, the choice of right technology has a great impact on a success of virtual teamworking. The technology needs to allow establishing effective communication and collaboration over space and time. Introducing the technology needed for virtual teamwork, the team leader has to considering number of factors, such as:
• resources • project’s budget
• information richness and social presence • people preference and experience
• project's requirements and their implication for support systems
There are two primary factors that can help virtual teams to evaluate apprehensive technology: (1) social presence and (2) information richness.
Type of task
Communication models
Generating Ideas, Plans and Data
Collecting
Problems with
Answers Problems withoutAnswers
Negotiating Technical or Interpersonal Conflicts
Only Audio Marginal fit Good fit Good fit Poor Fit
Only Video Poor Fit Good fit Good fit Marginal fit
Only Text - Chat Marginal Fit Good fit Good fit Poor Fit
Only Data (e.g.
e-mail, web-pages) Good fit Marginal fit Poor Fit Poor Fit
Table 1-4 Task/communication matrix (based on Duarte and Snyder 2001)
According to Cutkowsky et al. (1996) the virtual team's dependence on integrated communication technology requires these media links to be reliable, numerous, rapid, must support data and information transfer, generate shared interpretations of data and information, and the resolution of conflicts. Suchan and Hayzak (2001) argued that these communication links must support not only information transfer but also patterns of social relations in the form of mentoring, coaching, and conflict resolution, which develop team trust, member satisfaction, and commitment. The lack of the nonverbal communication may limit the team integration, members' feedback, and leads to complex and reiterative exchange of data (Strauss 1996) that can become the potential source of conflict in virtual teams (Montoya et al. 2001).
However, Stangor (2000) focused a paradox that the lack of face-to-face interaction or rich nonverbal communication may become the advantage of a virtual team. Without social influence the team members can be judged by their performance rather than on stereotypical cues.
1.7.1 Social Presence
Social presence is the degree to which the technology facilitates a personal connection with others (Duarte and Snyder 2001).
However, the high level of social presence is not necessary always better. Sometimes the low level of social presence may reduce interpersonal distractions, such as appearance, mannerism and being reminded of previous negative interactions with the person or group. The technologies with less social presence can be used for regular exchange of information between team members or other routine situations, while technologies with higher social presence may be suitable for non-routine situations containing high interpersonal or emotional components or ambiguity and uncertainty.
1.7.2 Information Richness
Technologies with high information richness are those that help to accurately transfer clues to the meaning of the communication and thereby reducing confusion and misunderstanding (VTASC 1999). Social presence can be defined by the amount and variety of information flowing through a specific communication media. Video conferencing is the technology that provides the highest level of information richness as it presents a large amount of information, such as spoken words, facial expressions, body language and environment information about each attendee’s surroundings. The other forms of communication such as e-mail or audio conference produce relatively lower level of information richness.
1.7.3 Other Factors
Apart from these two factors, other factors that influence the team’s selection of technology are as follows:
• Permanence - the degree to which the technology is capable of creating a historical
record of the team interactions or decisions.
• Experience and Familiarity with Virtual Operations - experienced virtual team
members often find high social presence or information-rich environment distracting and call them a waste of time.
• Time Constraints - there is often not sufficient time to select and procure the
optimal technology and to train people to use it.
• Access to Technological Training and Support - some technologies may not be
systems or the availability of hardware and software in certain parts of the organizations or in partner organizations.
• Symbolic Meaning - refers to the context (meaning) over and above the message that is
implied by the technology, such as receiving a hand-written thank-you letter rather than a typed one.
• Cost of implementation - refers to budget of the project and total cost of software,
hardware and training session
1.7.4 Available Technologies
The term groupware, which refers to electronic systems that integrate software and hardware, is used to describe the entire category of electronic tools available for the virtual team.
The following section describes the most popular groupware application outlined by Coleman (1997). The groupware can be divided into two general categories:
• synchronous - those that enable team members to interact at the same time . • asynchronous - those that facilitate delayed interaction
Synchronous groupware includes:
• Desktop and real-time data conferencing • Electronic meeting system (EMS) • Video conferencing
• Audio conferencing • Messaging systems
Asynchronous groupware includes: • E-mail
• Group calendars and Schedules • Bulletin boards and Web pages
• Non-real-time database sharing and conferencing • Workflow application
Purpose of meeting
Type of technology Ideas, Plans andGenerating Data Collecting
Problems with Answers
Problems without Answers
Negotiating Technical or Interpersonal Conflicts Desktop and real-time
conferencing (electronic
chat) useful useful least useful least useful
Multipoint, multimedia,
real-time data conferencing useful very useful very useful useful
Electronic Meeting System very useful useful useful useful
Electronic Display with
Voice useful useful useful least useful
Video Conferencing least useful useful useful useful
E-mail useful useful least useful least useful
Bulletin Boards and Web
Pages useful useful least useful least useful
Non-Real-Time Data
Conferencing useful useful least useful least useful
Table 1-5 The comparison of the communication tools for virtual teamworking (source: Duarte and Snyder 2001)
1.7.4.1 Desktop and real-time data conferencing
This groupware connects team members in synchronous interaction from their computer workstations. Such systems allow people to store common documents, and access to tools, including electronic chat and whiteboards.
Electronic chat allows team members to have typed conversations with other team members, where the questions, response and comments of all participants are visible in a chat window on each participant's desktop monitor (Duarte and Snyder 2001).
A whiteboard is the tool that allows team players to view a shared document, to diagram ideas on their computers and see the comments of other participants. Whiteboards are most effective with added communication links, such as audio, video, or the chat windows. The most advanced application of desktop and real-time conferencing includes full video and audio capabilities, which allows team members to see and hear each other. That multimedia solution is ideal for team tasks that require a high amount of information richness and social presence
1.7.4.2 Electronic meeting system (EMS)
[image:35.614.70.498.41.269.2]collaboration is steered by the team's facilitator, who should not restrict innovation or creativity, but guide the group to meet some specified objectives.
EMS becomes more compatible with other typical applications like word-processing, spreadsheet, or project management software. In spite of typical communication links such as e-mail, audio-video, chat, EMS provides additional tools to address typical tasks in teamworking such as brainstorming, voting, outlining or annotating.
EMS is the perfect software for teams that collaborate tightly and require a lot of meetings in which ideas can be generated, issues categorized and prioritised. Duarte and Snyder (2001) described the EMS as a technology that provides high level of social presence and information richness. However, those systems require a significant economic investment in software and organization culture, and there is a need for a skilled system's facilitator.
1.7.4.3 Videoconferencing
There are two types of video application:
• desktop video - the software and hardware are installed on team members machines, • specialized video facilities - the organization has specialized video rooms with video
equipment and high bandwidth networks to transmit full-motion video.
Video conferencing can provide high information richness and social presence. However the quality of the video picture strongly depends on the bandwidth, which is determined by the type of network, capacity of cables, speed of the computer modem, congestion in the network, etc.
1.7.4.4 Audio conferencing
1.7.4.5 Messaging systems
Those systems allow sending messages to other computers nearly in real time. Some of them have additional functions that allow its users:
• to find when virtual team members anywhere in the world are connected to the Internet, • to open a chat box to hold fully synchronous typed conversation,
• to transfer data and files between computers.
1.7.4.6 E-mail
E-mail is the most pervasive and successful computer groupware for distance collaboration. It is the electronic version of the postal service, generally accessible, cost effective, easy to learn, gives people time to think and consider their responses. Its advantages include fast, concise messaging with the added benefits of being able to send the same letter to a number of different people and distribute documents or/and files as attachments.
Most e-mail systems provide the possibility of tracking the source and journey of the original message. Moreover the systems can notify the receiver that a message was delivered and when opened, they even can filter and prioritise incoming messages
Duarte and Snyder (2001) described the e-mail as an excellent way to communicate and share information. However they point to the low information richness and lack social presence as the weakness of it.
1.7.4.7 Group calendars and Schedules
The need of time and work coordination makes calendaring and scheduling application very important for a virtual team. Following Coleman (1997) specification calendaring involves the manipulation of information on an individual's calendar while scheduling involves the coordination between individual calendars. Those tools are meant to be used for team coordination effort and they have no social presence or information richness. They are not adequate to resolve technical or interpersonal issues in the virtual team.
1.7.4.8 Bulletin boards and Web pages
discussions (Duarte and Snyder 2001). They are particular useful to present, share and gather large amounts of data. These methods allow people to build on, deliberate and comment on the ideas of others. A specialized database can be applied as a part of the application in team collaboration and project documentation.
These technologies have a low level of social presence although they are relatively inexpensive, easy to learn and maintain.
1.7.4.9 Non-real-time database sharing and conferencing
Shared database systems were one of the first groupware applications and they can be used to perform a number of information management functions, such as providing access to reference materials, stored data and documents, searching for relative information, updating documents, etc. Shared databases usually accept a wide range of data, including multimedia information. Information can be frequently distributed through involved participants. Individual team members have access to the database and freedom to search the database, or even in some cases the possibility to tailor the system for their own use.
Non-real-time databases contribute to permanence but have little social presence and information richness (Duarte and Snyder 2001)
1.7.4.10
Workflow application
Workflow applications are applied by organizations to repetitive business processes that involve similar sequential steps. These are rather very specialized solutions to optimise and automate workflow.
2 Research methodology and preliminary work
The previous chapter presents the literature review on the simulation methodology, teamworking and the impact of www technologies on simulation. In the next step of the research the author recognized a need to identify views and requirements of simulation practitioners on the subject.
The initial stage of this study was devoted to establishing an effective research methodology, which was motivated by the need to elicit knowledge, views, and predictions of people involved in simulation concerning the research questions.
The research methodology was composed of a questionnaire survey and a cross-sectional literature review that refers to the research subject. The rationale behind the selection of these techniques was determined by the nature of the first research questions being of an exploratory nature. That allowed the identifying of the next research operation and establishing the following research questions. Two multiple data collection techniques were deploying in order to maximise and strengthens data collected (Eisenhard 1989, Yin 1994, Denscombe 1998).
2.1 The research process
Gilbert (2001) described the research process as the two correlated methods (Figure 2-1): 1. Deduction - technique for the application of theory to process,
2. Induction - technique for generating theory from process analysing.
DEDUCTIVE APPROACH
THEORY EXPERIMENT PROCESS
INDUCTIIVE APPROACH
PROCESS EXPERIMENT THEORY
Figure 2-1 The research process
incomplete without both procedures and that in practise it is difficult to separate them. He also says that researchers do not have to complete every stage of the research process in a single project, and it is possible to move from observation to theory generation (inductive research) or to start with theory followed by testing (deductive research). Eisenhardt (1989) who stated that it is impossible to achieve an ideal of a clean theoretical state supported this opinion.
Table 2-1 presenting the detailed summary of deductive and inductive research features made by Gill and Johnson (1991).
Deductive methods Inductive methods
Explanation via analysis of casual relationship and Explanation o f subjective meaning systems and
explanation by covering-laws explanation by understanding
Generation and use o f quantitative data Generation and use of qualitative data
Use o f various controls, physical or statistical, so as to Commitment to research in everyday settings. To allow allow the testing o f hypnotises access to, and minimise reactivity among the subjects of
the research
Highly structured research methodology to ensure
replicability o f above characteristics Minimum structure as to ensure above characteristics
Laboratory experiments Quasi experiments Surveys Action Research Case Studies Ethnography
Table 2-1. Characteristics of deductive and inductive research (Gill & Johnson 1991)
2.2 Summary of the deployed research methods
2.2.1 Questionnaire Survey
Denscombe (1998) portrayed the survey approach as a research strategy, which principles allow effective mapping of the social world as well as the physical world. Some of the surveys’ crucial characteristics are:
□ Wide and inclusive coverage - it should have a wide coverage and panoramic point of view.
□ At specific point of time - it usually refers to the present state of affairs and involves an attempt to provide a snapshot of how things are at a specific time.
□ Empirical research - it involves looking for necessary information at source.
Surveys come in a wide variety of forms as: postal or email questionnaires, face to face or telephone interviews, etc.; and are used by researchers who can have different research aims and discipline backgrounds. Gill and Johnson (1991) focused on the fact that the nature of a survey depends highly on research objectives and the personal disposition of the researcher. They also distinguish two kinds of surveys - analytic and descriptive. The main aims of descriptive surveys are to generate a body of information from which insight and theory can be generated. In contrast, the analytic surveys’ main aims are to test out the validity of causal relationship.
Bryman (1988) presented a survey as a capable method of generating a number of quantitative and qualitative data by examining large numbers of people who are known to be representative of a wider population in order to test theories and hypothesis.
Qualitative research employs a variety of strategies and methods to collect and analyse a variety of empirical materials (Denzin & Lincoln 1994), which produce descriptive data. According to Bogdan and Taylor (1975) qualitative methods enable us to explore concepts whose essence is lost in other research approaches, such as people experience in their every day life. The task of the qualitative methodologist is to capture what people say and do as a product how they interpret and understand the events from the viewpoints of the participants. Bums (2000) in his book emphasises that qualitative research places stress on the validity of multiple meaning structures and holistic analysis, as opposed to the criteria of reliability and statistical compartmentalisation of quantitative research.
Although qualitative research has become a prominent strategy in some areas of science, it is by no means as pervasive as quantitative research, and according to Bryman (1988) and McNiff et al. (1998) the fusion of those two techniques can bring only better and more comprehensive results.
2.2.2 Questionnaire development and deployment
The questionnaire was the first method to be developed and deployed in the study. The aim of the survey was to collect data both qualitative and quantitative to answer the first research question. Collected information from this survey and literature review generated the route and next research step on which the study was conducted.
The objectives of the questionnaire were as follows:
□ To gather general information on practising modellers, for example their professions, and actual employment - it provides the basis for interpreting the data collected.
□ To investigate their opinions on the influence of the Internet technologies on simulation projects - it provides data to answer the first research questions.
□ To discover their opinions on the different Webbased solutions and future challenges -to indicate the path of the research.
A descriptive survey was done rather than an analytic one as there was no testing of the hypothesis but asking for personal opinions and experience.
The questionnaire survey was conducted over the Internet in the winter of 2000. Practitioners who participated in newsgroup comp.simulation received the survey with a request to participate. The newsgroup comp.simulation is the most popular group that gathers the people involved in all kind of computer simulation.
The questionnaire survey provided rich data concerning the current state of Web-based simulation and allowed the obtaining of opinions and expectations of people involved in simulation projects. The analysis of the survey results informed the direction of this research.
2.2.3 Questionnaire results
Table 3-2, Table 2-3 and Table 2-4 present the summary of data from questions addressing the background and profession, people’s previous experience in Web-based technologies, and their opinions.
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